Overview

Dataset statistics

Number of variables36
Number of observations193
Missing cells2453
Missing cells (%)35.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory54.4 KiB
Average record size in memory288.7 B

Variable types

Text2
Categorical8
Numeric15
Unsupported10
DateTime1

Alerts

Qty owned used has constant value ""Constant
Qty wanted has constant value ""Constant
Priority has constant value ""Constant
Qty owned is highly imbalanced (89.6%)Imbalance
Qty owned new is highly imbalanced (89.6%)Imbalance
Subtheme has 18 (9.3%) missing valuesMissing
Minifigs has 15 (7.8%) missing valuesMissing
Pieces has 3 (1.6%) missing valuesMissing
RRP (GBP) has 10 (5.2%) missing valuesMissing
RRP (USD) has 12 (6.2%) missing valuesMissing
RRP (CAD) has 102 (52.8%) missing valuesMissing
RRP (EUR) has 154 (79.8%) missing valuesMissing
EAN has 39 (20.2%) missing valuesMissing
UPC has 25 (13.0%) missing valuesMissing
Width has 9 (4.7%) missing valuesMissing
Height has 9 (4.7%) missing valuesMissing
Depth has 9 (4.7%) missing valuesMissing
Weight has 73 (37.8%) missing valuesMissing
Notes has 193 (100.0%) missing valuesMissing
Wanted has 193 (100.0%) missing valuesMissing
Flag 1 not used has 193 (100.0%) missing valuesMissing
Flag 2 not used has 193 (100.0%) missing valuesMissing
Flag 3 not used has 193 (100.0%) missing valuesMissing
Flag 4 not used has 193 (100.0%) missing valuesMissing
Flag 5 not used has 193 (100.0%) missing valuesMissing
Flag 6 not used has 193 (100.0%) missing valuesMissing
Flag 7 not used has 193 (100.0%) missing valuesMissing
Flag 8 not used has 193 (100.0%) missing valuesMissing
Value new (USD) has 2 (1.0%) missing valuesMissing
Value used (USD) has 9 (4.7%) missing valuesMissing
Launch date has 17 (8.8%) missing valuesMissing
Exit date has 17 (8.8%) missing valuesMissing
Number has unique valuesUnique
Notes is an unsupported type, check if it needs cleaning or further analysisUnsupported
Wanted is an unsupported type, check if it needs cleaning or further analysisUnsupported
Flag 1 not used is an unsupported type, check if it needs cleaning or further analysisUnsupported
Flag 2 not used is an unsupported type, check if it needs cleaning or further analysisUnsupported
Flag 3 not used is an unsupported type, check if it needs cleaning or further analysisUnsupported
Flag 4 not used is an unsupported type, check if it needs cleaning or further analysisUnsupported
Flag 5 not used is an unsupported type, check if it needs cleaning or further analysisUnsupported
Flag 6 not used is an unsupported type, check if it needs cleaning or further analysisUnsupported
Flag 7 not used is an unsupported type, check if it needs cleaning or further analysisUnsupported
Flag 8 not used is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-02-07 23:09:24.842671
Analysis finished2024-02-07 23:09:58.157899
Duration33.32 seconds
Software versionydata-profiling vv4.6.4
Download configurationconfig.json

Variables

Number
Text

UNIQUE 

Distinct193
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-02-08T00:09:58.528398image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Length

Max length9
Median length6
Mean length6.2797927
Min length6

Characters and Unicode

Total characters1212
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique193 ?
Unique (%)100.0%

Sample

1st row3569-1
2nd row3825-1
3rd row4191-1
4th row4476-1
5th row4722-1
ValueCountFrequency (%)
3569-1 1
 
0.5%
3825-1 1
 
0.5%
4855-1 1
 
0.5%
4191-1 1
 
0.5%
4476-1 1
 
0.5%
4722-1 1
 
0.5%
4754-1 1
 
0.5%
4757-1 1
 
0.5%
4758-1 1
 
0.5%
4762-1 1
 
0.5%
Other values (183) 183
94.8%
2024-02-08T00:09:59.168899image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 253
20.9%
- 193
15.9%
7 188
15.5%
9 90
 
7.4%
6 87
 
7.2%
5 81
 
6.7%
3 69
 
5.7%
0 68
 
5.6%
2 64
 
5.3%
8 63
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1019
84.1%
Dash Punctuation 193
 
15.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 253
24.8%
7 188
18.4%
9 90
 
8.8%
6 87
 
8.5%
5 81
 
7.9%
3 69
 
6.8%
0 68
 
6.7%
2 64
 
6.3%
8 63
 
6.2%
4 56
 
5.5%
Dash Punctuation
ValueCountFrequency (%)
- 193
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1212
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 253
20.9%
- 193
15.9%
7 188
15.5%
9 90
 
7.4%
6 87
 
7.2%
5 81
 
6.7%
3 69
 
5.7%
0 68
 
5.6%
2 64
 
5.3%
8 63
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1212
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 253
20.9%
- 193
15.9%
7 188
15.5%
9 90
 
7.4%
6 87
 
7.2%
5 81
 
6.7%
3 69
 
5.7%
0 68
 
5.6%
2 64
 
5.3%
8 63
 
5.2%

Theme
Categorical

Distinct23
Distinct (%)11.9%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
Star Wars
114 
City
16 
Castle
13 
Harry Potter
 
7
Marvel Super Heroes
 
6
Other values (18)
37 

Length

Max length24
Median length9
Mean length9.0310881
Min length4

Characters and Unicode

Total characters1743
Distinct characters40
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)5.2%

Sample

1st rowSports
2nd rowSpongeBob SquarePants
3rd rowPirates of the Caribbean
4th rowStar Wars
5th rowHarry Potter

Common Values

ValueCountFrequency (%)
Star Wars 114
59.1%
City 16
 
8.3%
Castle 13
 
6.7%
Harry Potter 7
 
3.6%
Marvel Super Heroes 6
 
3.1%
Indiana Jones 6
 
3.1%
Atlantis 5
 
2.6%
Aqua Raiders 3
 
1.6%
Super Mario 3
 
1.6%
Dino 2010 3
 
1.6%
Other values (13) 17
 
8.8%

Length

2024-02-08T00:09:59.390401image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
star 114
32.9%
wars 114
32.9%
city 16
 
4.6%
castle 13
 
3.8%
super 9
 
2.6%
harry 7
 
2.0%
potter 7
 
2.0%
marvel 6
 
1.7%
heroes 6
 
1.7%
indiana 6
 
1.7%
Other values (25) 48
13.9%

Most occurring characters

ValueCountFrequency (%)
a 297
17.0%
r 285
16.4%
t 178
10.2%
s 156
9.0%
153
8.8%
S 130
7.5%
W 114
 
6.5%
e 73
 
4.2%
i 47
 
2.7%
n 39
 
2.2%
Other values (30) 271
15.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1231
70.6%
Uppercase Letter 345
 
19.8%
Space Separator 153
 
8.8%
Decimal Number 12
 
0.7%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 297
24.1%
r 285
23.2%
t 178
14.5%
s 156
12.7%
e 73
 
5.9%
i 47
 
3.8%
n 39
 
3.2%
o 32
 
2.6%
l 28
 
2.3%
y 23
 
1.9%
Other values (12) 73
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
S 130
37.7%
W 114
33.0%
C 31
 
9.0%
H 13
 
3.8%
M 12
 
3.5%
A 10
 
2.9%
P 9
 
2.6%
I 7
 
2.0%
J 6
 
1.7%
B 5
 
1.4%
Other values (3) 8
 
2.3%
Decimal Number
ValueCountFrequency (%)
0 6
50.0%
1 3
25.0%
2 3
25.0%
Space Separator
ValueCountFrequency (%)
153
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1576
90.4%
Common 167
 
9.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 297
18.8%
r 285
18.1%
t 178
11.3%
s 156
9.9%
S 130
8.2%
W 114
 
7.2%
e 73
 
4.6%
i 47
 
3.0%
n 39
 
2.5%
o 32
 
2.0%
Other values (25) 225
14.3%
Common
ValueCountFrequency (%)
153
91.6%
0 6
 
3.6%
1 3
 
1.8%
2 3
 
1.8%
- 2
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1743
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 297
17.0%
r 285
16.4%
t 178
10.2%
s 156
9.0%
153
8.8%
S 130
7.5%
W 114
 
6.5%
e 73
 
4.2%
i 47
 
2.7%
n 39
 
2.2%
Other values (30) 271
15.5%

Subtheme
Categorical

MISSING 

Distinct50
Distinct (%)28.6%
Missing18
Missing (%)9.3%
Memory size1.6 KiB
The Clone Wars
35 
Episode III
15 
Episode VI
11 
Episode V
10 
Episode IV
 
9
Other values (45)
95 

Length

Max length30
Median length25
Mean length12.605714
Min length4

Characters and Unicode

Total characters2206
Distinct characters53
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)11.4%

Sample

1st rowFootball
2nd rowOn Stranger Tides
3rd rowEpisode VI
4th rowPhilosopher's Stone
5th rowPrisoner of Azkaban

Common Values

ValueCountFrequency (%)
The Clone Wars 35
18.1%
Episode III 15
 
7.8%
Episode VI 11
 
5.7%
Episode V 10
 
5.2%
Episode IV 9
 
4.7%
Fantasy Era 8
 
4.1%
Episode I 5
 
2.6%
The Mandalorian 4
 
2.1%
Miscellaneous 4
 
2.1%
Promotional 4
 
2.1%
Other values (40) 70
36.3%
(Missing) 18
 
9.3%

Length

2024-02-08T00:09:59.587403image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
episode 52
 
13.2%
the 45
 
11.4%
wars 35
 
8.9%
clone 35
 
8.9%
iii 15
 
3.8%
of 12
 
3.0%
vi 11
 
2.8%
v 10
 
2.5%
iv 9
 
2.3%
fantasy 8
 
2.0%
Other values (75) 162
41.1%

Most occurring characters

ValueCountFrequency (%)
e 221
 
10.0%
219
 
9.9%
o 185
 
8.4%
a 148
 
6.7%
s 146
 
6.6%
i 125
 
5.7%
r 118
 
5.3%
n 105
 
4.8%
l 103
 
4.7%
I 78
 
3.5%
Other values (43) 758
34.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1546
70.1%
Uppercase Letter 425
 
19.3%
Space Separator 219
 
9.9%
Decimal Number 7
 
0.3%
Other Punctuation 5
 
0.2%
Dash Punctuation 4
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 221
14.3%
o 185
12.0%
a 148
9.6%
s 146
9.4%
i 125
8.1%
r 118
7.6%
n 105
6.8%
l 103
6.7%
d 76
 
4.9%
t 76
 
4.9%
Other values (14) 243
15.7%
Uppercase Letter
ValueCountFrequency (%)
I 78
18.4%
E 62
14.6%
C 55
12.9%
T 44
10.4%
W 35
8.2%
V 31
 
7.3%
S 21
 
4.9%
M 18
 
4.2%
P 16
 
3.8%
F 15
 
3.5%
Other values (10) 50
11.8%
Decimal Number
ValueCountFrequency (%)
2 4
57.1%
4 1
 
14.3%
5 1
 
14.3%
3 1
 
14.3%
Other Punctuation
ValueCountFrequency (%)
' 3
60.0%
. 1
 
20.0%
: 1
 
20.0%
Space Separator
ValueCountFrequency (%)
219
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1971
89.3%
Common 235
 
10.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 221
 
11.2%
o 185
 
9.4%
a 148
 
7.5%
s 146
 
7.4%
i 125
 
6.3%
r 118
 
6.0%
n 105
 
5.3%
l 103
 
5.2%
I 78
 
4.0%
d 76
 
3.9%
Other values (34) 666
33.8%
Common
ValueCountFrequency (%)
219
93.2%
- 4
 
1.7%
2 4
 
1.7%
' 3
 
1.3%
4 1
 
0.4%
5 1
 
0.4%
3 1
 
0.4%
. 1
 
0.4%
: 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2206
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 221
 
10.0%
219
 
9.9%
o 185
 
8.4%
a 148
 
6.7%
s 146
 
6.6%
i 125
 
5.7%
r 118
 
5.3%
n 105
 
4.8%
l 103
 
4.7%
I 78
 
3.5%
Other values (43) 758
34.4%

Year
Real number (ℝ)

Distinct18
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2011.1554
Minimum2001
Maximum2024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-02-08T00:09:59.750901image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum2001
5-th percentile2004
Q12007
median2009
Q32012
95-th percentile2023
Maximum2024
Range23
Interquartile range (IQR)5

Descriptive statistics

Standard deviation6.4361191
Coefficient of variation (CV)0.0032002097
Kurtosis-0.61599986
Mean2011.1554
Median Absolute Deviation (MAD)3
Skewness0.88969784
Sum388153
Variance41.423629
MonotonicityNot monotonic
2024-02-08T00:09:59.915398image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
2008 24
12.4%
2007 20
10.4%
2006 18
9.3%
2009 18
9.3%
2011 16
8.3%
2023 16
8.3%
2022 16
8.3%
2005 14
7.3%
2010 14
7.3%
2012 11
5.7%
Other values (8) 26
13.5%
ValueCountFrequency (%)
2001 1
 
0.5%
2002 3
 
1.6%
2003 2
 
1.0%
2004 7
 
3.6%
2005 14
7.3%
2006 18
9.3%
2007 20
10.4%
2008 24
12.4%
2009 18
9.3%
2010 14
7.3%
ValueCountFrequency (%)
2024 2
 
1.0%
2023 16
8.3%
2022 16
8.3%
2021 7
 
3.6%
2020 3
 
1.6%
2017 1
 
0.5%
2012 11
5.7%
2011 16
8.3%
2010 14
7.3%
2009 18
9.3%
Distinct189
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-02-08T00:10:00.283398image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Length

Max length48
Median length34
Mean length20.341969
Min length5

Characters and Unicode

Total characters3926
Distinct characters66
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique185 ?
Unique (%)95.9%

Sample

1st rowGrand Soccer Stadium
2nd rowKrusty Krab
3rd rowCaptain's Cabin
4th rowJabba's Prize
5th rowGryffindor House
ValueCountFrequency (%)
battle 18
 
3.1%
starfighter 17
 
2.9%
the 15
 
2.6%
pack 13
 
2.2%
droid 13
 
2.2%
clone 11
 
1.9%
fighter 9
 
1.5%
9
 
1.5%
attack 8
 
1.4%
jedi 8
 
1.4%
Other values (334) 466
79.4%
2024-02-08T00:10:00.885420image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
394
 
10.0%
e 357
 
9.1%
a 307
 
7.8%
r 292
 
7.4%
t 257
 
6.5%
o 223
 
5.7%
i 215
 
5.5%
n 181
 
4.6%
l 134
 
3.4%
s 117
 
3.0%
Other values (56) 1449
36.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2829
72.1%
Uppercase Letter 602
 
15.3%
Space Separator 394
 
10.0%
Other Punctuation 42
 
1.1%
Dash Punctuation 27
 
0.7%
Decimal Number 26
 
0.7%
Open Punctuation 3
 
0.1%
Close Punctuation 3
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 357
12.6%
a 307
10.9%
r 292
10.3%
t 257
 
9.1%
o 223
 
7.9%
i 215
 
7.6%
n 181
 
6.4%
l 134
 
4.7%
s 117
 
4.1%
d 95
 
3.4%
Other values (14) 651
23.0%
Uppercase Letter
ValueCountFrequency (%)
T 66
 
11.0%
C 64
 
10.6%
S 60
 
10.0%
D 44
 
7.3%
A 43
 
7.1%
B 40
 
6.6%
G 28
 
4.7%
E 27
 
4.5%
P 27
 
4.5%
F 26
 
4.3%
Other values (14) 177
29.4%
Decimal Number
ValueCountFrequency (%)
1 8
30.8%
0 6
23.1%
3 3
 
11.5%
2 2
 
7.7%
5 2
 
7.7%
4 2
 
7.7%
6 1
 
3.8%
7 1
 
3.8%
9 1
 
3.8%
Other Punctuation
ValueCountFrequency (%)
' 28
66.7%
& 9
 
21.4%
: 3
 
7.1%
. 1
 
2.4%
, 1
 
2.4%
Space Separator
ValueCountFrequency (%)
394
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3431
87.4%
Common 495
 
12.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 357
 
10.4%
a 307
 
8.9%
r 292
 
8.5%
t 257
 
7.5%
o 223
 
6.5%
i 215
 
6.3%
n 181
 
5.3%
l 134
 
3.9%
s 117
 
3.4%
d 95
 
2.8%
Other values (38) 1253
36.5%
Common
ValueCountFrequency (%)
394
79.6%
' 28
 
5.7%
- 27
 
5.5%
& 9
 
1.8%
1 8
 
1.6%
0 6
 
1.2%
( 3
 
0.6%
) 3
 
0.6%
3 3
 
0.6%
: 3
 
0.6%
Other values (8) 11
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3926
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
394
 
10.0%
e 357
 
9.1%
a 307
 
7.8%
r 292
 
7.4%
t 257
 
6.5%
o 223
 
5.7%
i 215
 
5.5%
n 181
 
4.6%
l 134
 
3.4%
s 117
 
3.0%
Other values (56) 1449
36.9%

Minifigs
Real number (ℝ)

MISSING 

Distinct13
Distinct (%)7.3%
Missing15
Missing (%)7.8%
Infinite0
Infinite (%)0.0%
Mean3.8539326
Minimum1
Maximum21
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-02-08T00:10:01.063920image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q35
95-th percentile9
Maximum21
Range20
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.0011318
Coefficient of variation (CV)0.77871934
Kurtosis11.514084
Mean3.8539326
Median Absolute Deviation (MAD)1
Skewness2.7068432
Sum686
Variance9.0067924
MonotonicityNot monotonic
2024-02-08T00:10:01.244414image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
4 38
19.7%
1 34
17.6%
3 32
16.6%
2 27
14.0%
5 17
8.8%
6 9
 
4.7%
8 6
 
3.1%
9 5
 
2.6%
7 4
 
2.1%
21 2
 
1.0%
Other values (3) 4
 
2.1%
(Missing) 15
 
7.8%
ValueCountFrequency (%)
1 34
17.6%
2 27
14.0%
3 32
16.6%
4 38
19.7%
5 17
8.8%
6 9
 
4.7%
7 4
 
2.1%
8 6
 
3.1%
9 5
 
2.6%
10 1
 
0.5%
ValueCountFrequency (%)
21 2
 
1.0%
14 1
 
0.5%
12 2
 
1.0%
10 1
 
0.5%
9 5
 
2.6%
8 6
 
3.1%
7 4
 
2.1%
6 9
 
4.7%
5 17
8.8%
4 38
19.7%

Pieces
Real number (ℝ)

MISSING 

Distinct161
Distinct (%)84.7%
Missing3
Missing (%)1.6%
Infinite0
Infinite (%)0.0%
Mean439.82632
Minimum3
Maximum7541
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-02-08T00:10:01.447898image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile21.45
Q1102.5
median242.5
Q3451.75
95-th percentile1070.85
Maximum7541
Range7538
Interquartile range (IQR)349.25

Descriptive statistics

Standard deviation890.90132
Coefficient of variation (CV)2.0255753
Kurtosis43.043223
Mean439.82632
Median Absolute Deviation (MAD)154
Skewness6.2375561
Sum83567
Variance793705.16
MonotonicityNot monotonic
2024-02-08T00:10:01.659899image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
68 3
 
1.6%
79 3
 
1.6%
108 2
 
1.0%
155 2
 
1.0%
177 2
 
1.0%
268 2
 
1.0%
187 2
 
1.0%
214 2
 
1.0%
386 2
 
1.0%
675 2
 
1.0%
Other values (151) 168
87.0%
(Missing) 3
 
1.6%
ValueCountFrequency (%)
3 1
0.5%
6 1
0.5%
8 2
1.0%
13 1
0.5%
15 1
0.5%
16 1
0.5%
20 1
0.5%
21 2
1.0%
22 2
1.0%
23 1
0.5%
ValueCountFrequency (%)
7541 1
0.5%
6785 1
0.5%
6187 1
0.5%
3187 1
0.5%
1367 1
0.5%
1330 1
0.5%
1254 1
0.5%
1137 1
0.5%
1111 1
0.5%
1083 1
0.5%

RRP (GBP)
Real number (ℝ)

MISSING 

Distinct65
Distinct (%)35.5%
Missing10
Missing (%)5.2%
Infinite0
Infinite (%)0.0%
Mean42.649781
Minimum1.99
Maximum734.99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-02-08T00:10:01.877399image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum1.99
5-th percentile3.49
Q19.99
median24.99
Q344.99
95-th percentile89.99
Maximum734.99
Range733
Interquartile range (IQR)35

Descriptive statistics

Standard deviation88.378945
Coefficient of variation (CV)2.0722016
Kurtosis45.35799
Mean42.649781
Median Absolute Deviation (MAD)15
Skewness6.4352642
Sum7804.91
Variance7810.8379
MonotonicityNot monotonic
2024-02-08T00:10:02.251901image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
29.99 12
 
6.2%
14.99 12
 
6.2%
24.99 12
 
6.2%
9.99 10
 
5.2%
59.99 9
 
4.7%
19.99 7
 
3.6%
25.99 6
 
3.1%
8.99 6
 
3.1%
34.99 5
 
2.6%
2.99 5
 
2.6%
Other values (55) 99
51.3%
(Missing) 10
 
5.2%
ValueCountFrequency (%)
1.99 1
 
0.5%
2.45 1
 
0.5%
2.49 1
 
0.5%
2.99 5
2.6%
3.49 3
1.6%
3.89 1
 
0.5%
3.99 3
1.6%
4.99 3
1.6%
5.99 1
 
0.5%
6.85 1
 
0.5%
ValueCountFrequency (%)
734.99 2
 
1.0%
519.99 1
 
0.5%
344.99 1
 
0.5%
132.99 1
 
0.5%
129.99 1
 
0.5%
94.99 1
 
0.5%
91.99 1
 
0.5%
89.99 3
1.6%
84.99 2
 
1.0%
79.99 5
2.6%

RRP (USD)
Real number (ℝ)

MISSING 

Distinct45
Distinct (%)24.9%
Missing12
Missing (%)6.2%
Infinite0
Infinite (%)0.0%
Mean49.952928
Minimum3.49
Maximum849.99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-02-08T00:10:02.455899image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum3.49
5-th percentile4.99
Q111.99
median29.99
Q349.99
95-th percentile99.99
Maximum849.99
Range846.5
Interquartile range (IQR)38

Descriptive statistics

Standard deviation102.69323
Coefficient of variation (CV)2.0558
Kurtosis44.791525
Mean49.952928
Median Absolute Deviation (MAD)19.99
Skewness6.3935588
Sum9041.48
Variance10545.899
MonotonicityNot monotonic
2024-02-08T00:10:02.643415image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
19.99 16
 
8.3%
9.99 16
 
8.3%
29.99 13
 
6.7%
24.99 12
 
6.2%
39.99 11
 
5.7%
49.99 11
 
5.7%
30 6
 
3.1%
10 6
 
3.1%
69.99 6
 
3.1%
99.99 6
 
3.1%
Other values (35) 78
40.4%
(Missing) 12
 
6.2%
ValueCountFrequency (%)
3.49 4
 
2.1%
3.99 3
 
1.6%
4.99 4
 
2.1%
5 1
 
0.5%
5.99 1
 
0.5%
6.99 2
 
1.0%
7 2
 
1.0%
9 1
 
0.5%
9.99 16
8.3%
10 6
 
3.1%
ValueCountFrequency (%)
849.99 2
 
1.0%
599.99 1
 
0.5%
399.99 1
 
0.5%
139.99 2
 
1.0%
129.99 1
 
0.5%
119.99 1
 
0.5%
109.99 1
 
0.5%
99.99 6
3.1%
90 2
 
1.0%
89.99 5
2.6%

RRP (CAD)
Real number (ℝ)

MISSING 

Distinct31
Distinct (%)34.1%
Missing102
Missing (%)52.8%
Infinite0
Infinite (%)0.0%
Mean88.836154
Minimum4.99
Maximum1049.99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-02-08T00:10:02.816400image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum4.99
5-th percentile12.99
Q124.99
median39.99
Q382.49
95-th percentile179.99
Maximum1049.99
Range1045
Interquartile range (IQR)57.5

Descriptive statistics

Standard deviation173.75826
Coefficient of variation (CV)1.9559408
Kurtosis22.168573
Mean88.836154
Median Absolute Deviation (MAD)25
Skewness4.6249967
Sum8084.09
Variance30191.932
MonotonicityNot monotonic
2024-02-08T00:10:03.006899image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
39.99 8
 
4.1%
34.99 7
 
3.6%
14.99 7
 
3.6%
12.99 6
 
3.1%
24.99 6
 
3.1%
89.99 5
 
2.6%
29.99 4
 
2.1%
49.99 4
 
2.1%
64.99 4
 
2.1%
79.99 3
 
1.6%
Other values (21) 37
 
19.2%
(Missing) 102
52.8%
ValueCountFrequency (%)
4.99 3
1.6%
9.99 1
 
0.5%
12.99 6
3.1%
13.99 1
 
0.5%
14.99 7
3.6%
15.99 1
 
0.5%
19.99 2
 
1.0%
24.99 6
3.1%
26.99 1
 
0.5%
29.99 4
2.1%
ValueCountFrequency (%)
1049.99 2
 
1.0%
759.99 1
 
0.5%
499.99 1
 
0.5%
179.99 2
 
1.0%
159.99 1
 
0.5%
139.99 1
 
0.5%
129.99 3
1.6%
119.99 3
1.6%
99.99 3
1.6%
89.99 5
2.6%

RRP (EUR)
Real number (ℝ)

MISSING 

Distinct20
Distinct (%)51.3%
Missing154
Missing (%)79.8%
Infinite0
Infinite (%)0.0%
Mean118.29769
Minimum3.99
Maximum849.99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-02-08T00:10:03.173400image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum3.99
5-th percentile3.99
Q129.99
median64.99
Q389.99
95-th percentile624.99
Maximum849.99
Range846
Interquartile range (IQR)60

Descriptive statistics

Standard deviation202.79107
Coefficient of variation (CV)1.7142437
Kurtosis8.3174889
Mean118.29769
Median Absolute Deviation (MAD)30
Skewness2.9994443
Sum4613.61
Variance41124.219
MonotonicityNot monotonic
2024-02-08T00:10:03.330897image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
69.99 6
 
3.1%
29.99 4
 
2.1%
89.99 3
 
1.6%
34.99 3
 
1.6%
3.99 3
 
1.6%
849.99 2
 
1.0%
19.99 2
 
1.0%
64.99 2
 
1.0%
49.99 2
 
1.0%
99.99 2
 
1.0%
Other values (10) 10
 
5.2%
(Missing) 154
79.8%
ValueCountFrequency (%)
3.99 3
1.6%
9.99 1
 
0.5%
19.99 2
1.0%
20.99 1
 
0.5%
29.99 4
2.1%
34.99 3
1.6%
37.99 1
 
0.5%
49.99 2
1.0%
52.99 1
 
0.5%
59.99 1
 
0.5%
ValueCountFrequency (%)
849.99 2
 
1.0%
599.99 1
 
0.5%
399.99 1
 
0.5%
149.99 1
 
0.5%
104.99 1
 
0.5%
99.99 2
 
1.0%
89.99 3
1.6%
79.99 1
 
0.5%
69.99 6
3.1%
64.99 2
 
1.0%

EAN
Real number (ℝ)

MISSING 

Distinct154
Distinct (%)100.0%
Missing39
Missing (%)20.2%
Infinite0
Infinite (%)0.0%
Mean5.7020152 × 1012
Minimum5.702012 × 1012
Maximum5.7020176 × 1012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-02-08T00:10:03.513898image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum5.702012 × 1012
5-th percentile5.7020144 × 1012
Q15.7020145 × 1012
median5.7020145 × 1012
Q35.7020148 × 1012
95-th percentile5.7020174 × 1012
Maximum5.7020176 × 1012
Range5566322
Interquartile range (IQR)342358.5

Descriptive statistics

Standard deviation1159685.5
Coefficient of variation (CV)2.0338169 × 10-7
Kurtosis-0.13195876
Mean5.7020152 × 1012
Median Absolute Deviation (MAD)112470.5
Skewness1.0684064
Sum8.7811033 × 1014
Variance1.3448704 × 1012
MonotonicityNot monotonic
2024-02-08T00:10:03.717901image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5.702014366 × 10121
 
0.5%
5.702014601 × 10121
 
0.5%
5.702014601 × 10121
 
0.5%
5.702014601 × 10121
 
0.5%
5.702014601 × 10121
 
0.5%
5.702014519 × 10121
 
0.5%
5.702014519 × 10121
 
0.5%
5.702014368 × 10121
 
0.5%
5.702014517 × 10121
 
0.5%
5.702014841 × 10121
 
0.5%
Other values (144) 144
74.6%
(Missing) 39
 
20.2%
ValueCountFrequency (%)
5.702012018 × 10121
0.5%
5.702014152 × 10121
0.5%
5.702014152 × 10121
0.5%
5.702014152 × 10121
0.5%
5.702014259 × 10121
0.5%
5.702014262 × 10121
0.5%
5.702014364 × 10121
0.5%
5.702014365 × 10121
0.5%
5.702014365 × 10121
0.5%
5.702014366 × 10121
0.5%
ValueCountFrequency (%)
5.702017584 × 10121
0.5%
5.702017498 × 10121
0.5%
5.702017434 × 10121
0.5%
5.702017434 × 10121
0.5%
5.702017421 × 10121
0.5%
5.702017421 × 10121
0.5%
5.702017421 × 10121
0.5%
5.702017421 × 10121
0.5%
5.702017421 × 10121
0.5%
5.702017421 × 10121
0.5%

UPC
Real number (ℝ)

MISSING 

Distinct168
Distinct (%)100.0%
Missing25
Missing (%)13.0%
Infinite0
Infinite (%)0.0%
Mean6.6966597 × 1011
Minimum4.2884047 × 1010
Maximum6.7341939 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-02-08T00:10:03.910400image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum4.2884047 × 1010
5-th percentile6.7341904 × 1011
Q16.7341909 × 1011
median6.7341911 × 1011
Q36.7341916 × 1011
95-th percentile6.7341938 × 1011
Maximum6.7341939 × 1011
Range6.3053534 × 1011
Interquartile range (IQR)66450

Descriptive statistics

Standard deviation4.8646839 × 1010
Coefficient of variation (CV)0.07264344
Kurtosis168
Mean6.6966597 × 1011
Median Absolute Deviation (MAD)32770.5
Skewness-12.961481
Sum1.1250388 × 1014
Variance2.366515 × 1021
MonotonicityNot monotonic
2024-02-08T00:10:04.110898image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6.734190728 × 10111
 
0.5%
6.734191291 × 10111
 
0.5%
6.734191288 × 10111
 
0.5%
6.734191298 × 10111
 
0.5%
6.734191298 × 10111
 
0.5%
6.73419129 × 10111
 
0.5%
6.73419129 × 10111
 
0.5%
6.73419129 × 10111
 
0.5%
6.73419129 × 10111
 
0.5%
6.734191291 × 10111
 
0.5%
Other values (158) 158
81.9%
(Missing) 25
 
13.0%
ValueCountFrequency (%)
4.288404722 × 10101
0.5%
6.734190102 × 10111
0.5%
6.734190102 × 10111
0.5%
6.734190103 × 10111
0.5%
6.734190336 × 10111
0.5%
6.734190338 × 10111
0.5%
6.734190338 × 10111
0.5%
6.734190343 × 10111
0.5%
6.734190348 × 10111
0.5%
6.734190363 × 10111
0.5%
ValueCountFrequency (%)
6.734193895 × 10111
0.5%
6.734193842 × 10111
0.5%
6.73419379 × 10111
0.5%
6.73419379 × 10111
0.5%
6.73419377 × 10111
0.5%
6.73419377 × 10111
0.5%
6.73419377 × 10111
0.5%
6.734193769 × 10111
0.5%
6.734193769 × 10111
0.5%
6.734193769 × 10111
0.5%

Width
Real number (ℝ)

MISSING 

Distinct34
Distinct (%)18.5%
Missing9
Missing (%)4.7%
Infinite0
Infinite (%)0.0%
Mean31.702337
Minimum9.4
Maximum65.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-02-08T00:10:04.287400image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum9.4
5-th percentile12.706
Q119.1
median28.8
Q338.4
95-th percentile58.11
Maximum65.2
Range55.8
Interquartile range (IQR)19.3

Descriptive statistics

Standard deviation14.187101
Coefficient of variation (CV)0.44750964
Kurtosis-0.53764881
Mean31.702337
Median Absolute Deviation (MAD)9.6
Skewness0.4805422
Sum5833.23
Variance201.27385
MonotonicityNot monotonic
2024-02-08T00:10:04.458899image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
19.1 21
 
10.9%
38.2 19
 
9.8%
48 18
 
9.3%
28.8 14
 
7.3%
38.4 13
 
6.7%
19.2 10
 
5.2%
26.2 9
 
4.7%
14.4 9
 
4.7%
24 9
 
4.7%
28.19 7
 
3.6%
Other values (24) 55
28.5%
(Missing) 9
 
4.7%
ValueCountFrequency (%)
9.4 5
 
2.6%
9.5 2
 
1.0%
9.6 2
 
1.0%
12.46 1
 
0.5%
14.1 5
 
2.6%
14.4 9
4.7%
15.7 1
 
0.5%
19 1
 
0.5%
19.1 21
10.9%
19.2 10
5.2%
ValueCountFrequency (%)
65.2 6
 
3.1%
58.2 4
 
2.1%
57.6 3
 
1.6%
54 2
 
1.0%
53.3 1
 
0.5%
52.3 1
 
0.5%
49.9 1
 
0.5%
48.01 3
 
1.6%
48 18
9.3%
43.2 3
 
1.6%

Height
Real number (ℝ)

MISSING 

Distinct22
Distinct (%)12.0%
Missing9
Missing (%)4.7%
Infinite0
Infinite (%)0.0%
Mean24.225326
Minimum9.09
Maximum49.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-02-08T00:10:04.622898image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum9.09
5-th percentile12.4765
Q114.4
median26.2
Q328.8
95-th percentile38.4
Maximum49.9
Range40.81
Interquartile range (IQR)14.4

Descriptive statistics

Standard deviation8.9318639
Coefficient of variation (CV)0.36869943
Kurtosis-0.34450744
Mean24.225326
Median Absolute Deviation (MAD)7.1
Skewness0.35565578
Sum4457.46
Variance79.778193
MonotonicityNot monotonic
2024-02-08T00:10:04.794898image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
28.8 36
18.7%
26.2 25
13.0%
14.4 22
11.4%
14.1 17
8.8%
19.1 16
8.3%
38.4 11
 
5.7%
19.2 11
 
5.7%
35.4 8
 
4.1%
26.19 8
 
4.1%
28.2 6
 
3.1%
Other values (12) 24
12.4%
(Missing) 9
 
4.7%
ValueCountFrequency (%)
9.09 3
 
1.6%
9.1 1
 
0.5%
9.6 4
 
2.1%
10.6 1
 
0.5%
12.19 1
 
0.5%
14.1 17
8.8%
14.4 22
11.4%
15 2
 
1.0%
19.1 16
8.3%
19.2 11
5.7%
ValueCountFrequency (%)
49.9 1
 
0.5%
48 2
 
1.0%
46 1
 
0.5%
43.2 1
 
0.5%
38.4 11
 
5.7%
37.8 5
 
2.6%
35.4 8
 
4.1%
28.8 36
18.7%
28.2 6
 
3.1%
28.19 2
 
1.0%

Depth
Real number (ℝ)

MISSING 

Distinct39
Distinct (%)21.2%
Missing9
Missing (%)4.7%
Infinite0
Infinite (%)0.0%
Mean6.6719022
Minimum0.7
Maximum38.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-02-08T00:10:04.981400image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0.7
5-th percentile4.515
Q14.8
median6
Q37.2
95-th percentile9.6
Maximum38.5
Range37.8
Interquartile range (IQR)2.4

Descriptive statistics

Standard deviation4.0000189
Coefficient of variation (CV)0.599532
Kurtosis42.644795
Mean6.6719022
Median Absolute Deviation (MAD)1.2
Skewness5.8466333
Sum1227.63
Variance16.000151
MonotonicityNot monotonic
2024-02-08T00:10:05.174400image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
6 28
14.5%
4.6 26
13.5%
4.8 26
13.5%
7.2 17
8.8%
6.1 11
 
5.7%
7.1 11
 
5.7%
9.6 10
 
5.2%
5.7 5
 
2.6%
6.4 5
 
2.6%
8.79 3
 
1.6%
Other values (29) 42
21.8%
(Missing) 9
 
4.7%
ValueCountFrequency (%)
0.7 2
 
1.0%
2.8 1
 
0.5%
3.9 1
 
0.5%
4.04 3
 
1.6%
4.05 1
 
0.5%
4.4 1
 
0.5%
4.5 1
 
0.5%
4.6 26
13.5%
4.7 2
 
1.0%
4.8 26
13.5%
ValueCountFrequency (%)
38.5 1
 
0.5%
37.9 1
 
0.5%
23.8 1
 
0.5%
12.4 1
 
0.5%
11.8 2
 
1.0%
11.4 2
 
1.0%
9.6 10
5.2%
9.4 1
 
0.5%
9.1 3
 
1.6%
9 1
 
0.5%

Weight
Real number (ℝ)

MISSING 

Distinct71
Distinct (%)59.2%
Missing73
Missing (%)37.8%
Infinite0
Infinite (%)0.0%
Mean0.58264167
Minimum0.03
Maximum2.63
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-02-08T00:10:05.381899image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0.03
5-th percentile0.078
Q10.14
median0.37
Q30.78
95-th percentile2.128
Maximum2.63
Range2.6
Interquartile range (IQR)0.64

Descriptive statistics

Standard deviation0.60296558
Coefficient of variation (CV)1.0348824
Kurtosis2.9039543
Mean0.58264167
Median Absolute Deviation (MAD)0.26
Skewness1.8142323
Sum69.917
Variance0.36356749
MonotonicityNot monotonic
2024-02-08T00:10:05.584414image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.11 6
 
3.1%
0.03 5
 
2.6%
0.34 4
 
2.1%
0.78 4
 
2.1%
0.1 4
 
2.1%
0.12 4
 
2.1%
0.09 4
 
2.1%
0.14 3
 
1.6%
0.44 3
 
1.6%
0.19 3
 
1.6%
Other values (61) 80
41.5%
(Missing) 73
37.8%
ValueCountFrequency (%)
0.03 5
2.6%
0.04 1
 
0.5%
0.08 2
 
1.0%
0.09 4
2.1%
0.1 4
2.1%
0.11 6
3.1%
0.12 4
2.1%
0.13 3
1.6%
0.14 3
1.6%
0.15 3
1.6%
ValueCountFrequency (%)
2.63 1
0.5%
2.45 2
1.0%
2.38 1
0.5%
2.33 1
0.5%
2.28 1
0.5%
2.12 1
0.5%
2.04 1
0.5%
1.88 1
0.5%
1.75 1
0.5%
1.54 1
0.5%

Notes
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing193
Missing (%)100.0%
Memory size1.6 KiB

Qty owned
Categorical

IMBALANCE 

Distinct4
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
1
188 
2
 
3
7
 
1
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters193
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)1.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 188
97.4%
2 3
 
1.6%
7 1
 
0.5%
4 1
 
0.5%

Length

2024-02-08T00:10:05.761919image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-02-08T00:10:05.945900image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
1 188
97.4%
2 3
 
1.6%
7 1
 
0.5%
4 1
 
0.5%

Most occurring characters

ValueCountFrequency (%)
1 188
97.4%
2 3
 
1.6%
7 1
 
0.5%
4 1
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 193
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 188
97.4%
2 3
 
1.6%
7 1
 
0.5%
4 1
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Common 193
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 188
97.4%
2 3
 
1.6%
7 1
 
0.5%
4 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 193
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 188
97.4%
2 3
 
1.6%
7 1
 
0.5%
4 1
 
0.5%

Qty owned new
Categorical

IMBALANCE 

Distinct4
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
1
188 
2
 
3
7
 
1
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters193
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)1.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 188
97.4%
2 3
 
1.6%
7 1
 
0.5%
4 1
 
0.5%

Length

2024-02-08T00:10:06.108899image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-02-08T00:10:06.259899image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
1 188
97.4%
2 3
 
1.6%
7 1
 
0.5%
4 1
 
0.5%

Most occurring characters

ValueCountFrequency (%)
1 188
97.4%
2 3
 
1.6%
7 1
 
0.5%
4 1
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 193
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 188
97.4%
2 3
 
1.6%
7 1
 
0.5%
4 1
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Common 193
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 188
97.4%
2 3
 
1.6%
7 1
 
0.5%
4 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 193
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 188
97.4%
2 3
 
1.6%
7 1
 
0.5%
4 1
 
0.5%

Qty owned used
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
0
193 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters193
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 193
100.0%

Length

2024-02-08T00:10:06.408906image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-02-08T00:10:06.535924image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 193
100.0%

Most occurring characters

ValueCountFrequency (%)
0 193
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 193
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 193
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 193
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 193
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 193
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 193
100.0%

Wanted
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing193
Missing (%)100.0%
Memory size1.6 KiB

Qty wanted
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
0
193 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters193
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 193
100.0%

Length

2024-02-08T00:10:06.669398image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-02-08T00:10:06.797898image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
0 193
100.0%

Most occurring characters

ValueCountFrequency (%)
0 193
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 193
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 193
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 193
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 193
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 193
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 193
100.0%

Priority
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
1
193 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters193
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 193
100.0%

Length

2024-02-08T00:10:06.930399image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-02-08T00:10:07.238900image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
1 193
100.0%

Most occurring characters

ValueCountFrequency (%)
1 193
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 193
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 193
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 193
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 193
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 193
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 193
100.0%

Flag 1 not used
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing193
Missing (%)100.0%
Memory size1.6 KiB

Flag 2 not used
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing193
Missing (%)100.0%
Memory size1.6 KiB

Flag 3 not used
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing193
Missing (%)100.0%
Memory size1.6 KiB

Flag 4 not used
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing193
Missing (%)100.0%
Memory size1.6 KiB

Flag 5 not used
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing193
Missing (%)100.0%
Memory size1.6 KiB

Flag 6 not used
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing193
Missing (%)100.0%
Memory size1.6 KiB

Flag 7 not used
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing193
Missing (%)100.0%
Memory size1.6 KiB

Flag 8 not used
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing193
Missing (%)100.0%
Memory size1.6 KiB

Value new (USD)
Real number (ℝ)

MISSING 

Distinct190
Distinct (%)99.5%
Missing2
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean134.64372
Minimum2.8
Maximum863.65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-02-08T00:10:07.392900image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum2.8
5-th percentile9.735
Q141.55
median79.95
Q3156.06
95-th percentile463.235
Maximum863.65
Range860.85
Interquartile range (IQR)114.51

Descriptive statistics

Standard deviation153.92111
Coefficient of variation (CV)1.1431733
Kurtosis6.0153331
Mean134.64372
Median Absolute Deviation (MAD)44.85
Skewness2.3544882
Sum25716.95
Variance23691.707
MonotonicityNot monotonic
2024-02-08T00:10:07.583398image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
81.54 2
 
1.0%
259.43 1
 
0.5%
50.72 1
 
0.5%
79.95 1
 
0.5%
142.35 1
 
0.5%
39.53 1
 
0.5%
155.96 1
 
0.5%
112.05 1
 
0.5%
124.36 1
 
0.5%
9.54 1
 
0.5%
Other values (180) 180
93.3%
(Missing) 2
 
1.0%
ValueCountFrequency (%)
2.8 1
0.5%
3.73 1
0.5%
4.09 1
0.5%
5.33 1
0.5%
6.32 1
0.5%
6.73 1
0.5%
6.97 1
0.5%
7.1 1
0.5%
8.57 1
0.5%
9.54 1
0.5%
ValueCountFrequency (%)
863.65 1
0.5%
752.52 1
0.5%
747.81 1
0.5%
679.79 1
0.5%
663.99 1
0.5%
639.84 1
0.5%
505.02 1
0.5%
500 1
0.5%
481 1
0.5%
463.63 1
0.5%

Value used (USD)
Real number (ℝ)

MISSING 

Distinct183
Distinct (%)99.5%
Missing9
Missing (%)4.7%
Infinite0
Infinite (%)0.0%
Mean68.494185
Minimum2.04
Maximum617.34
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-02-08T00:10:07.768901image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum2.04
5-th percentile8.1435
Q123.1175
median40.745
Q374.03
95-th percentile213.023
Maximum617.34
Range615.3
Interquartile range (IQR)50.9125

Descriptive statistics

Standard deviation85.669044
Coefficient of variation (CV)1.2507492
Kurtosis16.508412
Mean68.494185
Median Absolute Deviation (MAD)21.75
Skewness3.5204213
Sum12602.93
Variance7339.1852
MonotonicityNot monotonic
2024-02-08T00:10:07.977901image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
47.32 2
 
1.0%
153.34 1
 
0.5%
5.22 1
 
0.5%
2.3 1
 
0.5%
2.04 1
 
0.5%
13.41 1
 
0.5%
12.82 1
 
0.5%
21.15 1
 
0.5%
31.07 1
 
0.5%
69.92 1
 
0.5%
Other values (173) 173
89.6%
(Missing) 9
 
4.7%
ValueCountFrequency (%)
2.04 1
0.5%
2.3 1
0.5%
2.45 1
0.5%
3.36 1
0.5%
4.8 1
0.5%
5.22 1
0.5%
5.53 1
0.5%
5.94 1
0.5%
7.36 1
0.5%
8.13 1
0.5%
ValueCountFrequency (%)
617.34 1
0.5%
576 1
0.5%
420.45 1
0.5%
325.43 1
0.5%
300.61 1
0.5%
269.42 1
0.5%
250 1
0.5%
233.99 1
0.5%
227.54 1
0.5%
214.13 1
0.5%

Launch date
Date

MISSING 

Distinct62
Distinct (%)35.2%
Missing17
Missing (%)8.8%
Memory size1.6 KiB
Minimum2001-01-09 00:00:00
Maximum2024-01-01 00:00:00
2024-02-08T00:10:08.189898image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-08T00:10:08.423920image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Exit date
Categorical

MISSING 

Distinct31
Distinct (%)17.6%
Missing17
Missing (%)8.8%
Memory size1.6 KiB
31/12/2009
17 
31/12/2010
15 
31/12/2012
15 
31/12/2008
14 
31/12/2024
13 
Other values (26)
102 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters1760
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)5.1%

Sample

1st row31/12/2007
2nd row31/12/2007
3rd row31/12/2012
4th row31/12/2003
5th row31/12/2002

Common Values

ValueCountFrequency (%)
31/12/2009 17
 
8.8%
31/12/2010 15
 
7.8%
31/12/2012 15
 
7.8%
31/12/2008 14
 
7.3%
31/12/2024 13
 
6.7%
31/12/2011 11
 
5.7%
31/12/2006 10
 
5.2%
31/12/2025 9
 
4.7%
31/12/2005 9
 
4.7%
31/12/2023 8
 
4.1%
Other values (21) 55
28.5%
(Missing) 17
 
8.8%

Length

2024-02-08T00:10:08.623908image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
31/12/2009 17
 
9.7%
31/12/2012 15
 
8.5%
31/12/2010 15
 
8.5%
31/12/2008 14
 
8.0%
31/12/2024 13
 
7.4%
31/12/2011 11
 
6.2%
31/12/2006 10
 
5.7%
31/12/2025 9
 
5.1%
31/12/2005 9
 
5.1%
31/12/2023 8
 
4.5%
Other values (21) 55
31.2%

Most occurring characters

ValueCountFrequency (%)
2 396
22.5%
1 392
22.3%
/ 352
20.0%
0 303
17.2%
3 193
11.0%
7 27
 
1.5%
4 22
 
1.2%
9 20
 
1.1%
8 20
 
1.1%
5 19
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1408
80.0%
Other Punctuation 352
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 396
28.1%
1 392
27.8%
0 303
21.5%
3 193
13.7%
7 27
 
1.9%
4 22
 
1.6%
9 20
 
1.4%
8 20
 
1.4%
5 19
 
1.3%
6 16
 
1.1%
Other Punctuation
ValueCountFrequency (%)
/ 352
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1760
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 396
22.5%
1 392
22.3%
/ 352
20.0%
0 303
17.2%
3 193
11.0%
7 27
 
1.5%
4 22
 
1.2%
9 20
 
1.1%
8 20
 
1.1%
5 19
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1760
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 396
22.5%
1 392
22.3%
/ 352
20.0%
0 303
17.2%
3 193
11.0%
7 27
 
1.5%
4 22
 
1.2%
9 20
 
1.1%
8 20
 
1.1%
5 19
 
1.1%

Interactions

2024-02-08T00:09:54.679675image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-08T00:09:26.786672image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-08T00:09:28.920175image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-08T00:09:31.024673image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-08T00:09:33.061671image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-08T00:09:34.956690image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-08T00:09:36.786688image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-08T00:09:38.774172image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-08T00:09:40.533175image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-08T00:09:42.424188image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-08T00:09:44.490176image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-08T00:09:46.535690image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-08T00:09:48.635690image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-08T00:09:50.852672image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-08T00:09:52.739673image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-08T00:09:54.797174image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-08T00:09:26.947174image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-08T00:09:29.077672image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-08T00:09:31.159175image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
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2024-02-08T00:09:35.070177image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
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2024-02-08T00:09:46.411674image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-08T00:09:48.504174image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-08T00:09:50.681173image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-08T00:09:52.618173image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-02-08T00:09:54.556690image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Missing values

2024-02-08T00:09:56.879673image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-02-08T00:09:57.557183image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

NumberThemeSubthemeYearSet nameMinifigsPiecesRRP (GBP)RRP (USD)RRP (CAD)RRP (EUR)EANUPCWidthHeightDepthWeightNotesQty ownedQty owned newQty owned usedWantedQty wantedPriorityFlag 1 not usedFlag 2 not usedFlag 3 not usedFlag 4 not usedFlag 5 not usedFlag 6 not usedFlag 7 not usedFlag 8 not usedValue new (USD)Value used (USD)Launch dateExit date
03569-1SportsFootball2006Grand Soccer Stadium14.0386.029.9949.99NaNNaNNaN6.734191e+1158.238.47.51.75NaN110NaN01NaNNaNNaNNaNNaNNaNNaNNaN259.43153.3401/01/200631/12/2007
13825-1SpongeBob SquarePantsNaN2006Krusty Krab3.0295.019.9919.99NaNNaNNaN6.734191e+1128.828.84.80.49NaN110NaN01NaNNaNNaNNaNNaNNaNNaNNaN232.1398.6501/06/200631/12/2007
24191-1Pirates of the CaribbeanOn Stranger Tides2011Captain's Cabin3.095.010.4911.9914.99NaN5.702015e+126.734192e+1119.114.14.60.13NaN110NaN01NaNNaNNaNNaNNaNNaNNaNNaN46.4831.8701/05/201131/12/2012
34476-1Star WarsEpisode VI2003Jabba's Prize2.040.05.997.00NaNNaN5.702014e+12NaN14.414.43.9NaNNaN110NaN01NaNNaNNaNNaNNaNNaNNaNNaN184.7050.1701/01/200331/12/2003
44722-1Harry PotterPhilosopher's Stone2001Gryffindor House1.068.08.9910.00NaNNaN5.702012e+124.288405e+1019.219.24.8NaNNaN110NaN01NaNNaNNaNNaNNaNNaNNaNNaN57.5034.7201/09/200131/12/2002
54754-1Harry PotterPrisoner of Azkaban2004Hagrid's Hut2.0302.019.9930.00NaNNaN5.702014e+126.734190e+1128.828.86.00.58NaN110NaN01NaNNaNNaNNaNNaNNaNNaNNaN121.2644.7005/04/200431/12/2005
64757-1Harry PotterPrisoner of Azkaban2004Hogwarts Castle9.0944.079.9990.00NaNNaN5.702014e+126.734190e+1157.638.49.62.12NaN110NaN01NaNNaNNaNNaNNaNNaNNaNNaN463.63190.4805/04/200431/12/2005
74758-1Harry PotterPrisoner of Azkaban2004Hogwarts Express4.0389.034.9940.00NaNNaN5.702014e+126.734190e+1133.628.87.20.79NaN110NaN01NaNNaNNaNNaNNaNNaNNaNNaN223.43120.6905/04/200431/12/2005
84762-1Harry PotterGoblet of Fire2005Rescue from the Merpeople5.0175.014.9920.00NaNNaN5.702014e+126.734191e+1119.228.84.80.30NaN110NaN01NaNNaNNaNNaNNaNNaNNaNNaN240.00103.5801/10/200531/07/2006
94766-1Harry PotterGoblet of Fire2005Graveyard Duel6.0548.029.9930.00NaNNaN5.702014e+126.734191e+1138.428.86.00.80NaN110NaN01NaNNaNNaNNaNNaNNaNNaNNaN365.59162.2701/10/200531/07/2006
NumberThemeSubthemeYearSet nameMinifigsPiecesRRP (GBP)RRP (USD)RRP (CAD)RRP (EUR)EANUPCWidthHeightDepthWeightNotesQty ownedQty owned newQty owned usedWantedQty wantedPriorityFlag 1 not usedFlag 2 not usedFlag 3 not usedFlag 4 not usedFlag 5 not usedFlag 6 not usedFlag 7 not usedFlag 8 not usedValue new (USD)Value used (USD)Launch dateExit date
18376191-1Marvel Super HeroesMiscellaneous2021Infinity GauntletNaN590.079.9979.9999.9989.995.702017e+126.734193e+1119.135.49.1NaNNaN110NaN01NaNNaNNaNNaNNaNNaNNaNNaN51.8139.4401/06/202131/12/2025
18476212-1Marvel Super HeroesBlack Panther2022Shuri's Lab2.058.08.999.9913.999.995.702017e+126.734194e+1115.714.14.5NaNNaN110NaN01NaNNaNNaNNaNNaNNaNNaNNaN6.73NaN01/10/202231/12/2023
18576217-1Marvel Super HeroesGuardians of the Galaxy Vol. 22022I am GrootNaN476.044.9954.9969.9949.995.702017e+126.734194e+1119.135.47.0NaNNaN110NaN01NaNNaNNaNNaNNaNNaNNaNNaN31.4926.4001/06/202231/12/2024
18676223-1Marvel Super HeroesAvengers: Endgame2022Nano GauntletNaN675.059.9969.9989.9969.995.702017e+126.734194e+1119.135.49.1NaNNaN110NaN01NaNNaNNaNNaNNaNNaNNaNNaN71.4749.0001/08/202231/12/2025
18776231-1Marvel Super HeroesSeasonal2022Guardians of the Galaxy Advent Calendar6.0268.029.9944.9959.9934.995.702017e+12NaN38.226.27.1NaNNaN110NaN01NaNNaNNaNNaNNaNNaNNaNNaN30.3320.0801/09/202231/12/2022
18876249-1Marvel Super HeroesMiscellaneous2023Venomized GrootNaN630.046.9949.9964.9952.995.702017e+126.734194e+1119.135.47.0NaNNaN110NaN01NaNNaNNaNNaNNaNNaNNaNNaN46.96NaN01/08/202331/12/2024
189912302-1Star WarsMagazine Gift2023Bo-Katan Kryze1.08.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN110NaN01NaNNaNNaNNaNNaNNaNNaNNaN8.578.72NaNNaN
190912310-1Star WarsMagazine Gift2023C-3PO & Gonk Droid2.015.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN110NaN01NaNNaNNaNNaNNaNNaNNaNNaN6.97NaNNaNNaN
1914293136-1Dino 2010NaN2006Parachute and MinifigureNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN110NaN01NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
1925000063-1Star WarsEpisode I2012TC-141.03.0NaNNaNNaNNaNNaN6.734192e+11NaNNaNNaNNaNNaN440NaN01NaNNaNNaNNaNNaNNaNNaNNaN120.69137.99NaNNaN